Computer Based Screening for Diabetic Retinopathy

基于计算机的糖尿病视网膜病变筛查

基本信息

批准号：
8855540
负责人：
Peter N Soliz
金额：
$ 62.33万
依托单位：
VISIONQUEST BIOMEDICAL, LLC
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-02-01 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8855540
关键词：
Address Algorithms American Applications Grants Automation Biometry Blindness Centers for Disease Control and Prevention (U.S.)Clinic Clinical Clinical Data Clinical Research Clinical Study Element Collection Communication Community Healthcare Computer software Computers Credentialing Data Data Collection Databases Devices Diabetes Mellitus Diabetic Retinopathy Disease Early Diagnosis Early treatment Effectiveness Ensure Environment Exercise Eye diseases Frequencies Goals Gold Grant Health Insurance Portability and Accountability Act Health Personnel Health Sciences Health Services Accessibility Healthcare Systems Image Incidence Individual Institutes Letters Manuals Masks Medical Medical Device Monitor New Mexico Ophthalmic examination and evaluation Optic Disk Phase Populations at Risk Process Productivity Quality of life Reader Reading Retina Retinal Retinal Diseases Risk Safety Screening Result Services Site Software Validation Solutions South Texas Specificity Staging System Techniques Technology Testing Texas Time Training Triage United States United States Food and Drug Administration Universities Validation adjudication base commercialization diabetic digital improved meetings safety testing screening software systems tv watching

项目摘要

DESCRIPTION (provided by applicant): The objective of this Phase II competitive renewal project is to implement a clinical study to collect data to validate EyeStar(tm), a software system as the basis for comprehensive telescreening for all stages of diabetic retinopathy (DR). According to the CDC, approximately 80 million people in the U.S. have some form of eye disease, including 20 million diabetics at risk for retinopathy. It is estimated that less than hal of those individuals with diabetes are screened periodically for DR. Lack of medical coverage and access to healthcare providers imposes major obstacles for nearly 10 million diabetics. Creating an affordable and accessible solution to providing screening services to these diabetics presents a significant challenge to the healthcare community. The objective of the original Phase II grant was to demonstrate a "top-down" screening algorithm for triaging normal, i.e. no disease, from suspect retinas using a new technique, amplitude modulation-frequency modulation (AM-FM), to analyze multi-field digital retinal images. As a result of the Phase II grant, the EyeStar(tm) software for diabetic retinopathy screening was developed. In this project, we will perform a clinical validation that will allow us to apply for 510(k) clearance by the Food and Drug Administration (FDA). To meet this goal, we have divided this proposal in three aims. In Aim #1, we will establish a clinical network and meet the requirements for the number of cases needed to perform a clinical study in order to obtain FDA clearance for our integrated, automatic screening system. In Aim #2, we will perform an independent validation for purposes of submitting to the FDA a 510(k) clearance application. In Aim #3, we will operate all the EyeStar(tm) components in a near "real-time" environment. This project is significant for two main reasons: increase of productivity and safety testing. Firs, by increasing the productivity of DR screening centers through automation, a much larger population of at-risk individuals will have access to this service, leading to improved productivit and quality of life through early detection and treatment. Second, by providing to the FDA a system that is highly effective and sensitive, we will insure that the safety requirements of semi-automatic screening for diabetic retinopathy are met. The FDA-cleared software will be integrated into our existing network of retinal screening sites in Texas and New Mexico as the first step toward commercialization.

描述（由申请人提供）：第二阶段竞争性更新项目的目标是实施一项临床研究，收集数据来验证 EyeStar(tm) 软件系统作为糖尿病视网膜病变（DR）各个阶段全面远程筛查的基础。据 CDC 称，美国约有 8000 万人患有某种形式的眼病，其中 2000 万糖尿病患者有患视网膜病变的风险。据估计，只有不到一半的糖尿病患者定期接受 DR 筛查。缺乏医疗保险和医疗保健提供者的获取给近 1000 万糖尿病患者带来了重大障碍。创建一种负担得起且易于使用的解决方案来为这些糖尿病患者提供筛查服务对医疗保健界来说是一项重大挑战。最初的第二阶段资助的目的是展示一种“自上而下”的筛查算法，使用新技术调幅-调频（AM-FM）对可疑视网膜进行正常（即无疾病）分类，以分析多场数字视网膜图像。作为第二阶段资助的结果，用于糖尿病视网膜病变筛查的 EyeStar(tm) 软件得以开发。在此项目中，我们将进行临床验证，以便我们能够申请美国食品和药物管理局 (FDA) 的 510(k) 许可。为了实现这一目标，我们将此提案分为三个目标。在目标 1 中，我们将建立一个临床网络，并满足进行临床研究所需的病例数量要求，以便获得 FDA 对我们的集成自动筛查系统的许可。在目标 2 中，我们将进行独立验证，以便向 FDA 提交 510(k) 许可申请。在目标 #3 中，我们将在近乎“实时”的环境中操作所有 EyeStar(tm) 组件。该项目之所以重要有两个主要原因：生产力的提高和安全测试。首先，通过自动化提高 DR 筛查中心的生产力，更多的高危人群将能够获得这项服务，从而通过早期检测和治疗提高生产力和生活质量。其次，通过向 FDA 提供高效、灵敏的系统，我们将确保满足糖尿病视网膜病变半自动筛查的安全要求。 FDA 批准的软件将集成到我们位于德克萨斯州和新墨西哥州的现有视网膜筛查站点网络中，作为商业化的第一步。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Multiscale AM-FM methods for diabetic retinopathy lesion detection.

DOI：
10.1109/tmi.2009.2037146
发表时间：
2010-02
期刊：
IEEE transactions on medical imaging
影响因子：
10.6
作者：
Agurto C;Murray V;Barriga E;Murillo S;Pattichis M;Davis H;Russell S;Abramoff M;Soliz P
通讯作者：
Soliz P